WordNet: a lexical database for English
Communications of the ACM
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
High performance question/answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
The automated acquisition of topic signatures for text summarization
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Experiments with interactive question-answering
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Incremental topic representations
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Using random walks for question-focused sentence retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
FERRET: interactive question-answering for real-world environments
COLING-ACL '06 Proceedings of the COLING/ACL on Interactive presentation sessions
Answering relationship queries on the web
Proceedings of the 16th international conference on World Wide Web
Modeling multi-step relevance propagation for expert finding
Proceedings of the 17th ACM conference on Information and knowledge management
Quality-aware collaborative question answering: methods and evaluation
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Selecting sentences for answering complex questions
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Complex question answering: unsupervised learning approaches and experiments
Journal of Artificial Intelligence Research
Semantic chunk annotation for complex questions using conditional random field
KRAQ '08 Coling 2008: Proceedings of the workshop on Knowledge and Reasoning for Answering Questions
Using scenario knowledge in automatic question answering
SumQA '06 Proceedings of the Workshop on Task-Focused Summarization and Question Answering
Using question classification to model user intentions of different levels
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Cancer stage prediction based on patient online discourse
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Using semantic information to answer complex questions
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
Preserving privacy on the searchable internet
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Discovering intermediate entities from two examples by using web search engine indices
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
An aspect-driven random walk model for topic-focused multi-document summarization
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
A web knowledge based approach for complex question answering
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Learning good decompositions of complex questions
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Improving the performance of the reinforcement learning model for answering complex questions
Proceedings of the 21st ACM international conference on Information and knowledge management
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We present a novel framework for answering complex questions that relies on question decomposition. Complex questions are decomposed by a procedure that operates on a Markov chain, by following a random walk on a bipartite graph of relations established between concepts related to the topic of a complex question and subquestions derived from topic-relevant passages that manifest these relations. Decomposed questions discovered during this random walk are then submitted to a state-of-the-art Question Answering (Q/A) system in order to retrieve a set of passages that can later be merged into a comprehensive answer by a Multi-Document Summarization (MDS) system. In our evaluations, we show that access to the decompositions generated using this method can significantly enhance the relevance and comprehensiveness of summary-length answers to complex questions.